About this Course

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100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 15 hours to complete

Suggested: 17 hours/week...

English

Subtitles: English

Skills you will gain

Machine LearningFinanceTradingInvestment

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 15 hours to complete

Suggested: 17 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1

Week 1

1 hour to complete

Introduction to Trading, Machine Learning and GCP

1 hour to complete
13 videos (Total 57 min), 1 reading, 3 quizzes
13 videos
Trading vs Investing6m
The Quant Universe2m
Quant Strategies7m
Quant Trading Advantages and Disadvantages4m
Exchange and Statistical Arbitrage8m
Index Arbitrage2m
Statistical Arbitrage Opportunities and Challenges5m
Introduction to Backtesting5m
Backtesting Design6m
What is AI and ML ? What is the difference between AI and ML?58s
Applications of ML in the Real World1m
What is ML?3m
1 reading
Welcome to Introduction to Trading, Machine Learning and GCP10m
3 practice exercises
Introduction to Trading5m
Python Skills Assessment Quiz
Intro to AI and ML5m
Week
2

Week 2

3 hours to complete

Supervised Learning and Forecasting

3 hours to complete
13 videos (Total 72 min)
13 videos
Regression and classification11m
Short history of ML: Linear Regression7m
Short history of ML: Perceptron5m
Lab Intro: Building a Regression Model37s
Introduction to Qwiklabs3m
Lab Walkthrough: Building a Regression Model9m
What is forecasting? - part 15m
What is forecasting? - part 24m
Choosing the right model and BQML - part 13m
Choosing the right model and BQML - part 22m
Lab Intro: Forecasting Stock Prices using Regression in BQML36s
Lab Walkthrough: Forecasting Stock Prices using Regression in BQML12m
1 practice exercise
Forecasting
Week
3

Week 3

2 hours to complete

Time Series and ARIMA Modeling

2 hours to complete
11 videos (Total 52 min)
11 videos
AR - Auto Regressive7m
MA - Moving Average2m
The Complete ARIMA Model4m
ARIMA compared to linear regression7m
How can you get a variety of models from just a single series?1m
How to choose ARIMA parameters for your trading model4m
Time Series Terminology: Auto Correlation4m
Sensitivity of Trading Strategy4m
Lab Intro: Forecasting Stock Prices Using ARIMA32s
Lab Walkthrough: Forecasting Stock Prices using ARIMA7m
1 practice exercise
Time Series
Week
4

Week 4

1 hour to complete

Introduction to Neural Networks and Deep Learning

1 hour to complete
9 videos (Total 36 min)
9 videos
Short history of ML: Modern Neural Networks8m
Overfitting and Underfitting6m
Validation and Training Data Splits4m
Why Google?1m
Why Google Cloud Platform?2m
What are AI Platform Notebooks1m
Using Notebooks1m
Benefits of AI Platform Notebooks2m
3 practice exercises
Model generalization
Google Cloud
Module Quiz8m
3.8
72 ReviewsChevron Right

Top reviews from Introduction to Trading, Machine Learning & GCP

By MSJan 30th 2020

Excellent! But, I am missing some of the prerequisites since I just wanted to take a chance and try things out, but feel like proceeding further might lead to some stumbling blocks.

By AAJan 13th 2020

Good course that gives a lot of breadth as an introduction to machine learning in finance. Well put together

Instructors

Instructor rating4.05/5 (42 Ratings)Info
Image of instructor, Jack Farmer

Jack Farmer 

Curriculum Director
New York Institute of Finance
11,733 Learners
7 Courses
Image of instructor, Ram Seshadri

Ram Seshadri 

Machine Learning Consultant
Google Cloud Platform
8,410 Learners
3 Courses

Offered by

Google Cloud logo

Google Cloud

New York Institute of Finance logo

New York Institute of Finance

About the Machine Learning for Trading Specialization

This Specialization is for finance professionals, including but not limited to: hedge fund traders, analysts, day traders, those involved in investment management or portfolio management, and anyone interested in gaining greater knowledge of how to construct effective trading strategies using Machine Learning. Alternatively, this specialization can be for machine learning professionals who seek to apply their craft to quantitative trading strategies. The courses will teach you how to create various trading strategies using Python. By the end of the Specialization, you will be able to create long-term trading strategies, short-term trading strategies, and hedging strategies. To be successful in this Specialization, you should have a basic competency in Python programming and familiarity with pertinent libraries for machine learning, such as Scikit-Learn, StatsModels, and Pandas. Experience with SQL will be helpful. You should have a background in statistics (expected values and standard deviation, Gaussian distributions, higher moments, probability, linear regressions) and foundational knowledge of financial markets (equities, bonds, derivatives, market structure, hedging)....
Machine Learning for Trading

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.